worker.fail
Report a structured failure and retry up to the job's configured attempt limit.
This record as markdown: /tools/visionmcp/worker.fail.md
What worker.fail does on Visionmcp
AI agents invoke worker.fail to trigger actions in Visionmcp. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why worker.fail is rated High
This tool triggers a failure report and initiates retry logic on a job, which is an external operation that modifies job state and causes re-execution. It doesn't merely read data, nor does it irreversibly delete anything — it causes side effects by altering job execution flow (failure recording + retry scheduling), placing it in the Execute category.
From the tool's definition Report a structured failure and retry up to the job's configured attempt limit.
Attacks that exploit this kind of access
The rule that runs worker.fail safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Visionmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For worker.fail, this is the rule to start with:
worker.fail stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Visionmcp, apply this rule, and every worker.fail call is checked against it from then on.
Questions about worker.fail
Report a structured failure and retry up to the job's configured attempt limit. It is categorised as a Execute tool in the Visionmcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Vision MCP server in PolicyLayer and add a rule for worker.fail: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Visionmcp. Nothing to install.
worker.fail is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the worker.fail rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for worker.fail. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
worker.fail is provided by the Vision MCP server (joshuahickscorp/visionmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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